Articles by Michael Penwarden | Synthical

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7

Kolmogorov n-Widths for Multitask Physics-Informed Machine Learning (PIML) Methods: Towards Robust Metrics

4 September 2024 by Michael Penwarden and others

Machine Learning, Computational Physics

A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions

18 September 2023 by Michael Penwarden and others

Computational Physics, Machine Learning

Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks

6 July 2023 by Shibo Li and others

Machine Learning, Computational Physics

Neural Operator Learning for Ultrasound Tomography Inversion

28 May 2023 by Haocheng Dai and others

Image and Video Processing, Computer Vision and Pattern Recognition

Deep neural operators can serve as accurate surrogates for shape optimization: A case study for airfoils

2 February 2023 by Khemraj Shukla and others

Fluid Dynamics, Artificial Intelligence

A Metalearning Approach for Physics-Informed Neural Networks (PINNs): Application to Parameterized PDEs

19 January 2023 by Michael Penwarden and others

Computational Physics, Machine Learning

Multifidelity Modeling for Physics-Informed Neural Networks (PINNs)

6 January 2023 by Michael Penwarden and others

Computational Physics, Machine Learning

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Machine Learning Computational Physics Image and Video Processing Computer Vision and Pattern Recognition Fluid Dynamics Artificial Intelligence Optimization and Control